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Development of Fast Prediction System of User Action for a Fully Autonomous Smart Home System 4

Development of Fast Prediction System of User Action for a F...

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4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Rajalakshmi, N.R. Sharmila, L. Prabu, S. Veeramakali, T. Arulkumaran, G. Chourasia, Pranshu Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu India School of Computing Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Chennai India School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Kattankulathur Chennai India School of Computing and Information Technology Reva University Karnataka Bangalore560064 India

ISBN: (纸本)9798331523923

the HVAC system, energy storage building, distributed power supply, and other equipment are integrated into the scheduling algorithm, which is aimed at reducing household electricity consumption. It is also assumed that users can provide energy to the grid according to their own conditions. Taking electricity cost and comfort level as optimization targets, a home energy optimization control model for the coordinated management of hybrid energy sources is built. A smart scheduling mechanism based on the improved adaptive particle swarm optimization approach is proposed in order to derive the best time intervals for electric appliances, necessary power for the control of the room temperature for every time frame, and power for charging and discharging of the storage battery at various moments. Simulation results show that through the incorporation of distributed photovoltaic power generation, backup storage by battery, and home energy optimization control, the system efficiently balances between user comfort and electricity consumption. this offers great technical support to the development of home energy management systems. By using time-of-use electricity price for energy acquisition and supply, the optimization control goal is minimizing both power use and cost as well as preserving comfort levels. the hybrid energy management's proposed home energy optimization control model uses an adaptive particle swarm optimization algorithm to find the optimal operation schedules of the electrical appliances, the required power for temperature control in a room, and the charge/discharge power level of the storage battery at each time interval. As per the optimization principle, the proposed dynamic programming algorithm converts the multi-stage problem into a sequence of single-stage problems and solves them separately. this method successfully resolves intricate problems that cannot be addressed through greedy algorithms or divide-and-conquer. In this research, management ac

关键词： Decision making

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Multi-class Generative Adversarial Network for Hyperspectral Image Classification for Addressing Class Imbalance Problem 4th

Multi-class Generative Adversarial Network for Hyperspectral...

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4th international conference on Smart IoT Systems: Innovations and Computing, SSIC 2023

作者： Kumar, Deepak Kumar, Dharmender Department of Computer Science and Engineering Guru Jambheshwar University of Science and Technology Haryana Hisar India

ISBN: (纸本)9789819751990

Class-imbalanced datasets are commonly observed in hyperspectral image classification and deep learning models often tend to demonstrate a bias toward the dominant class, resulting in very low efficiency for minority classes. Data augmentation has been the most widely used strategy to mitigate class-imbalanced challenge. therefore, in this paper, the authors have introduced a data augmentation approach utilizing a multi-class generative adversarial network (MCGAN) to deal with this issue. In the proposed approach a generative adversarial network is utilized to specifically generate fake minority class samples and integrating these samples with the existing class samples. Further, a convolutional neural network (CNN) has been employed for classification of hyperspectral image samples. A series of experiments, utilizing the proposed approach, has been conducted with two most popular and publicly available datasets. the experiment results obtained are then compared with four state-of-the-art data augmentation techniques. the comparison results prove the supremacy of the proposed approach in terms of the quality of the generated samples and the classification accuracy over the state-of-the-art techniques. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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A DIY C-T spectrometer and its application in FBG temperature sensing demodulation 4

A DIY C-T spectrometer and its application in FBG temperatur...

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4th international Computational Imaging conference, CITA 2024

作者： Wang, Tengfei Tao, Chuanyi Wang, Yu Li, Jingke Wang, Jingting Feng, Cheng School of Science Chongqing University of Technology Chongqing400054 China School of Clinical Medicine Chongqing Medical and Pharmaceutical College Chongqing400030 China

ISBN: (纸本)9781510688834

Fiber optic sensing technology offers efficient and accurate monitoring across various applications. A key component in this technology is the spectrometer, which is essential for high-precision measurement of physical quantities by analyzing optical signal spectra. this study investigates the use of a spectrometer to measure wavelength drift in Fiber Bragg Gratings (FBGs) caused by temperature variations, aiming to enhance temperature sensing accuracy and reliability. An unfolded asymmetric Czerny-Turner (C-T) near-infrared spectrometer was designed for this purpose. the initial spectrometer structure was developed using aberration cancellation theory, followed by optical configuration optimization through software simulations. A spectrometer system was then assembled on an optical platform, with wavelength calibration and spectral measurement functionalities implemented via a graphical programming environment. Performance testing with various light sources demonstrated that the system achieves a resolution of better than 0.5 nm in the 1525-1565 nm wavelength range and better than 2 nm in the 1298-1565 nm range. the spectrometer was subsequently used in a temperature sensing system with FBGs. Experimental results confirmed that the developed spectrometer effectively tracks FBG wavelength shifts due to temperature changes. this study provides valuable insights into the application of spectrometers for fiber optic sensing and their role in accurate demodulation. © 2025 SPIE.

关键词： Fiber Bragg gratings

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A path planning algorithm based on multi-factor cost pruning optimization 4

A path planning algorithm based on multi-factor cost pruning...

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2024 4th international conference on Intelligent Traffic Systems and Smart City, ITSSC 2024

作者： Li, Wangwang Yin, Dejun School of Mechanical Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781510686304

Addressing the obstacle avoidance path planning problem for intelligent vehicles, this paper proposes a dynamic path planning method based on multi-factor cost pruning optimization. this method enhances planning efficiency while ensuring safety by pruning decisions using a multi-factor cost function combined with dynamic programming principles. Specifically, it selects key obstacles based on the dynamic window division according to vehicle speed and integrates factors such as obstacle cost and road boundary cost to calculate decision priority. Additionally, an evaluation function is designed to assess the environment's complexity by considering the proportion of obstacles in the dynamic window relative to the window area, distribution, dynamic characteristics, road conditions, and other factors. the pruning proportion is dynamically adjusted based on environmental complexity to maintain safety and maximize planning efficiency. Experimental results indicate that this method can promptly respond to environmental changes, optimize planning efficiency, ensure path safety and rationality, and demonstrate high practical applicability and effectiveness. through these innovative methods and experimental results, this paper provides significant technical support and theoretical guidance for the field of intelligent vehicle path planning, highlighting its broad application prospects and scientific research value. © 2025 SPIE.

关键词： Motion planning

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Measuring API Usability and the Environment: A YouTube API Case Study 37th

Measuring API Usability and the Environment: A YouTube API C...

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37th international conference on Computer Applications in Industry and engineering

作者： Alanazy, Sultan Tian, Jeff Southern Methodist Univ Dept Comp Sci Dallas TX 75205 USA Imam Abdulrahman Bin Faisal Univ Coll Comp Sci & Info Tech Dammam Saudi Arabia

ISBN: (纸本)9783031762727;9783031762734

Application programming Interface (API) plays a vital role in Cloud computing. Improving API usability will help application programmers select and adapt the most suitable APIs for their specific needs. By adopting a general framework for usability measurement and analyzing questions and answers on Stack Overflow for YouTube APIs, we define three direct usability metrics: "team response time" to quantify learnability, "net upvote" to measure user satisfaction, and "downvote" to reflect usability problems. In addition, we identify six environmental factors that influence API usability by analyzing the question tags: language, library, browser, operating system, integrated development environment, and device. Our measurement and analysis provide an objective assessment of API usability and its environmental influencing factors.

关键词： API (Application programming interface) usability metrics Stack Overflow YouTube API empirical study

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GPU Acceleration of the Enhanced Jaya Optimization Algorithm for Solving Large Systems of Nonlinear Equations 4th

GPU Acceleration of the Enhanced Jaya Optimization Algorit...

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4th international conference on Numerical Computations: theory and Algorithms, NUMTA 2023

作者： Silva, Bruno Guerreiro Lopes, Luiz Doctoral Program in Informatics Engineering University of Madeira Madeira Island Funchal Portugal Regional Secretariat for Education Science and Technology Regional Government of Madeira Funchal Portugal Faculty of Exact Sciences and Engineering University of Madeira Madeira Island Funchal9020-105 Portugal

ISBN: (纸本)9783031812408

this paper presents a GPU-based parallel implementation of the Enhanced Jaya (EJAYA) algorithm for solving large-scale systems of nonlinear equations. EJAYA is a gradient-free metaheuristic optimization scheme based on the population-based parameter-less Jaya algorithm that has recently been shown to be capable of solving nonlinear equation systems, a class of challenging problems that are difficult to solve by traditional approaches, particularly as systems become larger. the proposed parallel algorithm was implemented using the Julia programming language on a high-performance GeForce RTX 3090 GPU with 10 496 CUDA cores and 24 GB GDDR6X VRAM and was tested using a set of difficult scalable nonlinear equation system problems. the obtained results, with average speedups up to 122.25x, evidenced the capability of the proposed GPU-based parallel algorithm to meet the computational demands of the important class of problems under consideration. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Optimization algorithms

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Technology Enhanced Teaching for an Industry 4.0 Economy - A case of engineering tuition in an ODL university 16

Technology Enhanced Teaching for an Industry 4.0 Economy - A...

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16th international conference on Society and Information Technologies, ICSIT 2025

作者： Lugoma, Masikini Mosia, Ngaka Ilunga, Masengo Department of Mining Minerals and Geomatics Engineering University of South Africa Pretoria South Africa Department of Industrial Engineering and Engineering Management University of South Africa Pretoria South Africa Department of Civil and Environmental Engineering and Building Science University of South Africa Pretoria South Africa

ISBN: (纸本)9781950492831

the mission of engineering technology education is to produce technologists who can work with current technology. therefore, engineering curricula must be a combination of applied engineering theory and hands-on instruction. Courses on mechanical drawing and design of engineering equipment must be core in the instruction of engineering technologists. engineering design is a linear and morphological process that requires a hands-on approach to instruction. It is mission-critical for engineering technology instruction to emphasize more on synthesis as opposed to analysis, that is, course content must include design thinking-related courses rather than scientific analysis and mathematical modeling. this research paper presents a comprehensive example that illustrates how 3IR (Industrial Revolution) skills can be increased in Industrial engineering instruction. the research employs the use of Lego designs, machine learning, and programming languages. the result manifesting is that engineering graduates acquire a capability in engineering equipment production, automation, and design innovation, indispensable for the 4IR economy. © 2025 international conference on Society and Information Technologies. All Rights Reserved.

关键词： engineering education

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Minimizing the Maximum Link Utilization for Traffic engineering in SDN: A Comparative Analysis 4

Minimizing the Maximum Link Utilization for Traffic Engineer...

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4th international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2024

作者： Prabu, U. Geetha, V. Department of Computer Science and Engineering Puducherry Technological University Puducherry605014 India Department of Information Technology Puducherry Technological University Puducherry605014 India

Software Defined Network modernizes network architecture by supporting scalability, significant flexibility, and programmability. Its functioning has been extended to several areas such as cloud computing, edge computing, enterprise networks, data centers, and the Internet of things (IoT). It also successfully enhances the functioning of traffic engineering. Traffic engineering involves optimization and dynamic control of traffic flows, minimizing congestion and maximum link utilization, centralized control, and network traffic management. It also enables the effective utilization of resources, boosts the user experience, and increases network performance. Minimizing maximum link utilization implies the distribution of network traffic across respective links or paths to use the offered resources of the network by preventing congestion. Its major goal is to guarantee that none of the individual links gets overloaded. Various approaches have been proposed in the past several years to address this problem. In this article, the state-of-the-art approaches are reviewed and analyzed. the problem formulation of each approach for minimizing the maximum link utilization is detailed with significant importance. the proposed algorithms, its type, and results are also depicted to have a better comparative analysis. Additionally, the type of graph considered while formulating the problem, topologies used to investigate the efficiency of the algorithm, performance metrics, and implementation platforms are listed to have a clear understanding of various approaches. © 2025 the Authors. Published by Elsevier B.V.

关键词： Deep reinforcement learning

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Towards Reproducible Research in Machine Learning via Blockchain 4th

Towards Reproducible Research in Machine Learning via Bloc...

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4th international conference on Numerical Computations: theory and Algorithms, NUMTA 2023

作者： Filatovas, Ernestas Stripinis, Linas Orts, Francisco Paulavičius, Remigijus Vilnius University Institute of Data Science and Digital Technologies Akademijos 4 Vilnius08663 Lithuania

ISBN: (纸本)9783031812460

artificial Intelligence, particularly in Machine Learning and related research areas such as Operational Research, currently faces a reproducibility crisis. Researchers encounter difficulties reproducing key results due to lacking critical details, including the disconnection between publications and the associated codes, data, and parameter settings. Solutions that improve code accessibility, data provenance tracking, research transparency, auditing of obtained results, and trust can significantly accelerate algorithm and model development, validation, and transition into real-world applications. Blockchain technology, with its features of decentralization, data immutability, cryptographic hash functions, and consensus algorithms, provides a promising avenue for developing such solutions. By leveraging the distributed ledger working over a peer-to-peer network, a secure and auditable infrastructure can be established for sharing and controlling data in a trusted manner. Our analysis examines the current state-of-the-art blockchain-based proposals that target reproducibility issues in the Machine Learning domain. Based on the analysis of existing solutions, we propose a high-level architecture and main modules for developing a blockchain-based platform that enhances reproducible research in Machine Learning and can be adapted to other artificial Intelligence domains. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Distributed ledger

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Research on visualization of minority music knowledge graph based on Neo4j 24

Research on visualization of minority music knowledge graph ...

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7th international conference on Information science and Systems, ICISS 2024

作者： Mao, ChunXia Wen, ShuangBing Liu, Hong Hu, Tao Li, Jun College of Intelligent Systems Science and Engineering Hubei Minzu University China Hubei Engineering Research Center of Selenium Food Nutrition and Health Intelligent Technology Hubei Minzu University China School of Music and Dance Hubei Minzu University China The Key Laboratory of Performing Art Equipment and System Technology Ministry of Culture and Tourism Hubei Minzu University China

ISBN: (纸本)9798400717567

the digital age has created various channels for the sustainable development of traditional culture. A Neo4j-based knowledge graph for Tujia Intangible cultural heritage music was constructed to address the potential loss of Tujia Intangible cultural heritage music. the project involved integrating and consolidating Tujia Intangible cultural heritage music resources, organizing and cleaning the collected data, storing it in a Neo4j graph database, designing a knowledge base ontology model, and completing the construction of the Tujia Intangible cultural heritage music knowledge graph. the knowledge graph makes the knowledge of music and cultural heritage explicit from vast information resources, effectively expanding its dissemination breadth and promoting the protection and inheritance of intangible cultural heritage music in ethnic areas. © 2024 Copyright held by the owner/author(s).

关键词： Knowledge graph

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